When I want to get dense layer from the network when doing train, got the following error. How do fix this?
My input: self.input_var = T.tensor3('inputs') self.target_var = T.ivector('targets') get out of dense layer: self.util_add_dense(self.dense1_sz) self.dense1_out = lasagne.layers.get_output(self.network, deterministic=True) self.dense1 = theano.function([self.input_var], [self.dense1_out]) in train function: dense1 = networkrel.dense1(inputs) Traceback (most recent call last): File "relational_network.py", line 211, in <module> semantic_ae.network_train() File "relational_network.py", line 203, in network_train utility_train(self, self.training_inputs, self.training_targets, self.test_inputs, self.test_targets) File "/home/relational_network_utilities.py", line 91, in utility_train dense = networkrel.dense1(inputs, targets) File "/root/miniconda2/lib/python2.7/site-packages/theano/compile/function_module.py", line 813, in __call__ allow_downcast=s.allow_downcast) File "/root/miniconda2/lib/python2.7/site-packages/theano/tensor/type.py", line 140, in filter raise TypeError(err_msg) TypeError: Bad input argument to theano function with name "relational_network.py:113" at index 0 (0-based). Backtrace when that variable is created: File "relational_network.py", line 209, in <module> semantic_ae.network_build_layers_v1() File "relational_network.py", line 104, in network_build_layers_v1 self.network_inp_prepare() File "relational_network.py", line 89, in network_inp_prepare self.input_var = T.tensor3('inputs') TensorType(float32, 3D) cannot store a value of dtype float64 without risking loss of precision. If you do not mind this loss, you can: 1) explicitly cast your data to float32, or 2) set "allow_input_downcast=True" when calling "function". Value: "array([[[0. , 0. , 0. , ..., 0. , -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to theano-users+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/theano-users/dda37f68-6849-49f3-9d5d-14d08175905f%40googlegroups.com.